SSRN Author: William T. SchererWilliam T. Scherer SSRN Contenthttp://www.ssrn.com/author=1838742
http://www.ssrn.com/rss/en-usSun, 20 Sep 2015 01:42:43 GMTeditor@ssrn.com (Editor)Sun, 20 Sep 2015 01:42:43 GMTwebmaster@ssrn.com (WebMaster)SSRN RSS Generator 1.0REVISION: Effects of Limit Order Book Information Level on Market Stability MetricsUsing an agent-based model of the limit order book, we explore how the levels of information available to participants, exchanges, and regulators can be used to improve our understanding of the stability and resiliency of a market. Ultimately, we want to know if electronic market data contains previously undetected information that could allow us to better assess market stability. Using data produced in the controlled environment of an agent-based model’s limit order book, we examine various resiliency indicators to determine their predictive capabilities. Most of the types of data created have traditionally been available either publicly or on a restricted basis to regulators and exchanges, but other types have never been collected. We confirmed our findings using actual order flow data with user identifications included from the CME (Chicago Mercantile Exchange) and New York Mercantile Exchange (NYMEX). Our findings strongly suggest that high-fidelity microstructure data in ... http://www.ssrn.com/abstract=2648457
http://www.ssrn.com/1429604.htmlSat, 19 Sep 2015 12:22:38 GMTREVISION: Effects of Limit Order Book Information Level on Market Stability MetricsUsing an agent-based model of the limit order book, we explore how the levels of information available to participants, exchanges, and regulators can be used to improve our understanding of the stability and resiliency of a market. Ultimately, we want to know if electronic market data contains previously undetected information that could allow us to better assess market stability. Using data produced in the controlled environment of an agent-based model’s limit order book, we examine various resiliency indicators to determine their predictive capabilities. Most of the types of data created have traditionally been available either publicly or on a restricted basis to regulators and exchanges, but other types have never been collected. We confirmed our findings using actual order flow data with user identifications included from the CME (Chicago Mercantile Exchange) and New York Mercantile Exchange (NYMEX). Our findings strongly suggest that high-fidelity microstructure data in ... http://www.ssrn.com/abstract=2648457
http://www.ssrn.com/1422193.htmlSat, 22 Aug 2015 10:59:22 GMT